A linked-data paradigm for the integration of static and dynamic building data in Digital Twins

Dimitris Mavrokapnidis, Kyriakos Katsigarakis, Pieter Pauwels, Ekaterina Petrova, Ivan Korolija, Dimitrios Rovas

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

18 Citations (Scopus)

Abstract

Digital Twins is an emerging field of research, mainly because they span the entire building lifecycle promising to uncover hidden inefficiencies and deliver data-driven applications. Broadly defined as real-time digital representations of physical assets, Digital Twins require a connection between static and real-time data. However, building information is usually stored in different formats across the lifecycle, making data integration a challenging task. We hereby often rely on linked data technologies, yet overall system integration approaches with multiple types of data sources. In this work, a data linking methodology is proposed to combine static building design data from Industry Foundation Classes (IFC) and dynamic data using the Brick Schema; a domain ontology which configures data analytics applications during the operational phase. To facilitate this integration, we develop a tool to facilitate the linking of building topology, product, and sensor data using the two schemata. The implementation of our methodology in a real test case demonstrates its significance in combining diverse data sources which can be an important step for the delivery of Digital Twin applications.
Original languageEnglish
Title of host publicationBuildSys 2021 - Proceedings of the 2021 ACM International Conference on Systems for Energy-Efficient Built Environments
PublisherAssociation for Computing Machinery, Inc
Pages369-372
Number of pages4
ISBN (Electronic)9781450391146
DOIs
Publication statusPublished - 17 Nov 2021
Event1st ACM International Workshop on Big Data and Machine Learning for
Smart Buildings and Cities
- Coimbra, Portugal
Duration: 17 Nov 202118 Nov 2021

Workshop

Workshop1st ACM International Workshop on Big Data and Machine Learning for
Smart Buildings and Cities
Country/TerritoryPortugal
CityCoimbra
Period17/11/2118/11/21

Funding

FundersFunder number
Marie Skłodowska‐Curie
European Union's Horizon 2020 - Research and Innovation Framework Programme860555
European Commission958310

    Keywords

    • Ontologies
    • Linked Data
    • Semantic Web Technologies
    • BOT
    • IFC
    • Brick
    • Metadata
    • OWL
    • RDF
    • Smart Buildings
    • Digital Twins
    • metadata
    • semantic web technologies
    • smart buildings
    • digital twins
    • brick
    • linked data
    • ontologies

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